Raman spectroscopy based measurements in patterned structures

ABSTRACT

A method for use in measuring one or more characteristics of patterned structures, the method including providing measured data comprising data indicative of at least one Raman spectrum obtained from a patterned structure under measurements using at least one selected optical measurement scheme each with a predetermined configuration of at least one of illuminating and collected light conditions corresponding to the one or more characteristics to be measured, processing the measured data, and determining, for each of the at least one Raman spectrum, a distribution of Raman-contribution efficiency (RCE) within at least a part of the structure under measurements, being dependent on characteristics of the structure and the predetermined configuration of the at least one of illuminating and collected light conditions in the respective optical measurement scheme, and analyzing the distribution of Raman-contribution efficiency and determining the one or more characteristics of the structure.

TECHNOLOGICAL FIELD

The present invention is in the field of metrology techniques, andrelates to a method and system for measuring variousparameters/properties of patterned structures, such as semiconductorwafers, using Raman spectroscopy based measurements.

BACKGROUND

The growing complexity of semiconductor device designs in advancedtechnology nodes involves not only a decrease in structural dimensionsand higher complexity of the device design, but also the utilization ofnew materials. Device yield and performance become increasinglysensitive to material properties, such as composition, stress,crystallinity and doping, which in turn require appropriate metrologicalsolutions for process control.

Various optical measurement techniques have been developed for measuringthe strain and other properties of a material.

U.S. Pat. No. 7,274,440 describes systems and methods for measuringstress in a specimen. One system includes an optical subsystemconfigured to measure stress-induced birefringence in patternedstructures formed on the specimen. In some embodiments, the opticalsubsystem may be configured as a spectroscopic ellipsometer, amulti-angle laser ellipsometer, a polarimeter, a polarizedreflectometer, or some combination thereof. The system also includes aprocessor coupled to the optical subsystem. The processor is configuredto determine stress in a material of the patterned structures using thestress-induced birefringence measurements. One method includes measuringstress-induced birefringence in patterned structures formed on thespecimen using an optical technique. The method also includesdetermining stress in a material of the patterned structures using thestress-induced birefringence measurements.

GENERAL DESCRIPTION

The present invention provides a novel approach for measuring variousstructure parameters, especially useful for controlling the process ofstructure manufacture. This is based on the inventors' understandingthat, although some technologies, such as (X-ray Diffraction (XRD),High-Resolution X-ray Diffraction (HRXRD), X-ray Fluorescence (XRF),X-ray Photoelectron Spectroscopy (XPS), Low energy Electron inducedX-ray Emission Spectrometry (LEXES), provide relevant information aboutthe patent structure's parameters, there is a need for a good solutionwhich adequately satisfies the stringent sensitivity and throughputrequirements for controlling the manufacture of patterned structures, inparticular semiconductor process control.

The present invention presents a novel methodology for advancedcharacterization of semiconductor structures' properties (generally,patterned structures). Example for such properties are materialcomposition, stress and doping.

The invention is based on using Raman Spectroscopy at specificmeasurement configurations (e.g. polarization configurations), typicallyin conjunction with suitable modeling capabilities, in order tohighlight and isolate sensitivity to the parameters of interest, as wellas to distinguish between sensitivity to different material parameters.

Raman spectroscopy is an established technology, with extensiveliterature describing its usage for the characterization of variousmaterial properties. However, as described more specifically below,correct control over illumination and collection channels attributes, aswell as the accompanying signal processing and modeling tools, arecritical to enable accurate measurements using this method.

The Raman spectrum carries information on various properties of theprobed sample. Most notably, different peaks in the spectrum correspondto different materials. When the measured target is comprised ofmaterial compounds (e.g. SiGe), specific peaks in the Raman spectrumwould correspond to different atom pairs (e.g. Si—Si, Si—Ge and Ge—Ge).

In this connection, reference is made to FIG. 1 exemplifying the Ramanspectrum from a thin SiGe layer deposited over Si (graph S₁), as well aspure (bulk) Si for reference (graph S₂). In the SiGe measurement, fourpeaks are clearly observed. The strong peak at 520 cm⁻¹ corresponds toSi—Si vibrations in the substrate. The three additional peaks correspondto Si—Si, Si—Ge and Ge—Ge pairs in the SiGe film. In the pure-Sireference spectrum, only the substrate Si—Si peak is observed. Thus, thepresence of a SiGe layer gives rise to three additional peaks,associated with the vibrations of different atom pairs in the layer.

Methods for extracting information on concentration and stress from thepositions of these peaks are well known in the literature. For example,a set of equations relating the positions of the three SiGe peaks withthe Germanium composition and the layer stress, is presented in thefollowing publication: T. S. Perov et al., Composition and strain inthin Si ₁-xGex virtual substrates measured by micro-Raman spectroscopyand x-ray diffraction, J. App. Phys. 109, 033502 (2011).

Doping is another characteristic which affects the Raman spectrum.Carrier concentration, arising from the dopant distribution, affects theRaman signal and causes an additional\shift in the Raman peaks. Thelevel of doping can hence be incorporated into the fitting procedure,and concurrent assessment of doping level along with stress andcomposition is possible through monitoring peak locations (see forexample—A. Perez-Rodriguez et al., Effect of stress and composition onthe Raman spectra of etch-stop SiGeB layers, J. Appl. Phys. 80, 15(1996).

The present invention provides a novel metrology method and device,configured to allow optimized Raman-metrology for the samplecharacteristics of interest. This approach allows access to multipleproperties of the sample, and specifically applies also to metrology ofnanostructured devices.

Also, the present invention provides a set of modeling solutions(methods and systems) to allow correct utilization of these methods anddegrees of freedom in the device configuration, as well as accurateinterpretation of the Raman measurements.

The above two aspects of the invention can be used separately, withsubstantial potential benefit to either. Conversely, used together theycan lead to significantly improved metrological performance, as will bediscussed below.

Thus, according to one broad aspect of the invention, it provides amethod for use in measuring one or more characteristics of patternedstructures. The method comprises:

providing measured data comprising data indicative of at least one Ramanspectrum obtained from a patterned structure under measurements using atleast one selected optical measurement scheme each with a predeterminedconfiguration of at least one of illuminating and collected lightconditions corresponding to said one or more characteristics to bemeasured;

processing the measured data, and determining, for each of said at leastone Raman spectrum, a distribution of Raman-contribution efficiencyacross at least a part of the structure under measurements, beingdependent on characteristics of the structure and said predeterminedconfiguration of the at least one of illuminating and collected lightconditions in the respective optical measurement scheme;

analyzing said distribution of Raman-contribution efficiency anddetermining said one or more characteristics of the structure.

The one or more characteristics of the structure to be measuredcomprises at least one of the following: dimension, materialcomposition, stress, crystallinity.

The predetermined configuration of the illuminating and collected lightconditions is characterized by selecting at least one of the following(possibly separately for illumination and collection): excitationwavelength; polarization; retardation; light beam shape; angulardistribution of the illuminating light; and wavefront of light.

In some embodiments, the measured data is indicative of a number n (n>1)of Raman spectra obtained from the patterned structure undermeasurements using the number n of the optical measurement schemeshaving n different configurations of the illuminating and collectedlight conditions. The processing of the measured data includes:calculating, for each i-th Raman spectrum of the n Raman spectra, thedistribution of Raman-contribution efficiency, RCEi(x,y,z), across theat least part of the structure under measurements; and selecting one ormore distributions of the Raman-contribution efficiency corresponding tothe one or more characteristics to be measured; and determining saidcharacteristic(s) of the structure from the selected distribution(s). Toclarify, the RCE represents the spatial distribution of the contributionto the Raman signal. It depends on the coupling of electromagneticradiation into the structure, the excitation of the Raman signal insidethe structure and coupling of the excited radiation to the detectionsystem.

The measured data comprising the number n of Raman spectra is obtainedin n measurement sessions using the n optical measurement schemes,respectively. Such n measurement schemes may be performed successively;or at least some of such measurement schemes may be performedconcurrently.

In another broad aspect of the invention, it provides a method for usein measuring one or more characteristics of patterned structures, themethod comprising:

applying a number n of two or more different optical measurement schemesto a patterned structure and determining measured data comprisingcorresponding n Raman spectra from said patterned structure, said noptical measurement schemes differing from one another in at least onecondition of either one or both of illuminating and collected light;

processing the measured data and determining said one or morecharacteristics of said structure, said processing comprisingdetermining n Raman-contribution efficiency distributions, RCE₁(x,y,z),RCE₂(x,y,z), . . . RCE_(n)(x,y,z), across at least a part of thestructure for said n Raman spectra respectively, each of saidRaman-contribution efficiency distributions being dependent oncharacteristics of the structure and the respective optical measurementscheme, thereby enabling determination of said one or morecharacteristics of the structure.

In some embodiments, the method of the invention further includesselection of an optimal measurement scheme for determination of one ormore characteristics of interest in the patterned structure undermeasurements. This is implemented by interpreting the Raman-contributionefficiency corresponding to one or more of the preceding measurementschemes and optimizing the configuration of the at least one of theilluminating and collecting light conditions (i.e. optimizing themeasurement scheme(s)) for one or more of the successive measurementschemes to be applied to the at least part of the patterned structure.

In yet another broad aspect, the invention provides a control system foruse in measuring one or more characteristics of patterned structures.The control system comprises:

a processor unit configured to receive and process measured datacomprising data indicative n Raman spectra obtained from a patternedstructure under measurements using n optical measurement scheme eachwith a different configuration of illuminating and collected lightconditions corresponding to said one or more characteristics to bemeasured, said processing of the measured data comprising determining nRaman-contribution efficiency distributions, RCE₁(x,y,z), RCE₂(x,y,z), .. . RCE_(n)(x,y,z), across at least a part of the structure, for said nRaman spectra respectively, each of said Raman-contribution efficiencydistributions being dependent on characteristics of the structure andthe respective optical measurement scheme, thereby enablingdetermination of said one or more characteristics of the structure froma selected one or more of said n Raman-contribution efficiencydistributions.

The control system may also include at least one of illuminationcontroller and collection controller configured and operable tocontrollably vary at least one of the illuminating and collecting lightconditions by varying at least one of the following: excitationwavelength; polarization; retardation; light beam shape; angularpropagation of the illuminating light; angular propagation of the lightbeing collected; and wavefront of light.

The invention also provides a system for use in measuring one or morecharacteristics of patterned structures, the system comprising: anoptical measurement system configured and operable to perform a number nof different optical measurement schemes on a patterned structure anddetermining measured data comprising corresponding n Raman spectra fromsaid patterned structure, said n optical measurement schemes differingfrom one another in at least one condition of either one or both ofilluminating and collected light; and the above-described controlconfigured for data communication with the optical measurement system toreceive and process the measured data and determine the one or morecharacteristics of the patterned structure under measurements.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to better understand the subject matter that is disclosedherein and to exemplify how it may be carried out in practice,embodiments will now be described, by way of non-limiting example only,with reference to the accompanying drawings, in which:

FIG. 1 exemplifies the Raman spectrum from two samples, one being a thinSiGe layer deposited over Si, and the other being a pure bulk Si;

FIG. 2 exemplifies effect of polarization on relative intensity of thesingle-phonon and two-phonon peaks in Si;

FIGS. 3a to 3c exemplify position-dependence of the contribution to themain-Si-peak in the Raman signal, for a simple grating structure, whereFIG. 3c schematically illustrates a modeled structure formed by SiO₂layer on a patterned Si layer; and FIG. 3a and FIG. 3b show measuredRaman signals from Si grating, corresponding to, respectively,wavelengths of λ=405 nm and λ=532 nm;

FIG. 4 shows a flow diagram of the Raman spectroscopy model-based methodof the invention for use in measurements in patterned structures;

FIG. 5 showing a block diagram of a system of the invention for carryingout the method of FIG. 4 for interpreting Raman metrology measured data(and possibly also managing Raman metrology measurements); and

FIG. 6 illustrates a specific but not limiting example of theconfiguration of the optical measurement system allowing considerableflexibility of measurement schemes, to be used with the control systemof FIG. 5.

DETAILED DESCRIPTION OF EMBODIMENTS

As indicated above, the present invention is based on the use of RamanSpectroscopy at specific configuration(s) of at least one ofillumination and light collection conditions (e.g. polarization(s),excitation wavelength, retardation, light beam shape, angularpropagation of the illuminating/collected light, etc.), and preferablyin conjunction with suitable modeling capabilities. This techniqueprovides for highlighting and isolating sensitivity to the parameters ofinterest, and for distinguishing between sensitivity to differentmaterial parameters.

The following is the description of optimized Raman metrology scheme,according to some embodiments of the invention.

Raman spectroscopy represents a unique type of light-matter interaction.Different parts of the Raman spectrum have different responses to achange in the optical scheme, specifically: change(s) in illuminationand collection polarizations \retardations, change(s) in illuminationand collection angle(s) of incidence and pupils shape, wavefronts andfocus.

As an example for the possible benefit from correct manipulation of oneor more of these parameters, let us consider the issue of two-phononbackground. As described previously, the Raman spectrum from pure bulkSi presents a sharp peak at about 520 cm⁻¹. An additional, very broadand significantly weaker, spectral peak is observed at 230 cm⁻¹-380cm⁻¹. This weak Raman signal arises from a 2-phonon process.

In most cases, the weak Raman signal associated with the 2-photonprocess is not of interest for the metrology. However, this signal actsas a background signature which can significantly affect (and confound)the interpretation of the Raman spectrum. The relative intensity betweenthe 1-phonon peaks and the 2-phonon peak can be modified by severalorders of magnitude through correct control over the illumination andcollection polarizations.

This dependence is illustrated in FIG. 2, exemplifying effect ofpolarization on relative intensity of the single-phonon and two-phononpeaks in Si. Two graphs are shown P₁ and P₂, where two polarizationconfigurations are presented, i.e. illumination and collectionpolarizations P_(ill)∥P_(coll) (graph P₁) and P_(ill)⊥P_(coll) (graphP₂). As shown in the figure, when the illumination and collectionpolarizations P_(ill) and P_(coll) are tuned perpendicular to eachother, and both are oriented at 45° to the crystal lattice of a sample,a 3 orders of magnitude suppression of the 2-phonon peak is observed.Thus, by aligning the illumination polarization P_(ill) in direction 45°to the crystal structure, and aligning the collection polarizationP_(coll) perpendicular to illumination polarization, the 2-phonon signalis significantly reduced, compared to having the polarizationsco-aligned.

This is only one example for how correct polarization manipulation cangreatly improve the signal quality and the ability to isolate importantmeasurement components from those which are not of interest (of lessinterest). As will be described below, the same principle can be used tohighlight sensitivity to specific parameters of interest.

Such a simple approach is not practical (and even might be impossible)to be applied to a measured target which is not a planar film but ratheris structured. The electromagnetic field distribution inside a structurecan be very complicated, and depends on the structure dimensions as wellas material characteristics.

The present invention provides for implementing such highlighting ofsensitivity and background suppression for not-only blanket targets butrather also on-structure measurements. This can be accomplished byhardware control as well as by utilizing modeling tools to correctlyoptimize the measurement scheme.

The following are some specific but not limiting examples for suchmeasurement scheme optimization. These examples include: (i) profilingthe measured characteristics across the structure: profiling informationcan be obtained across z (depth profiling), or even full profiling ofthe measured properties at different locations (x, y and z) across thestructure; (ii) metrology measurements of separate stress componentsinside a structure; (iii) use of modeling/algorithmic tools forduring-measurement-feedback; (iv) dimensional metrology.

(i) Profiling of the Measured Characteristics Across the Structure

Raman spectroscopy provides an integral measurement over the probedtarget: the measured signal averages over the entire measurement spot,and over the penetration depth into the sample. It is often of greatinterest to be able to identify the distribution of the measuredcharacteristic across the structure, both as a function of depth and oflateral position (“profiling”).

It is a common practice to use multiple wavelengths in order to changethe penetration depth. The penetration depth dependence on wavelength isvery sharp, allowing good resolving capabilities for such profilingmethod. Penetration depths into Si at normal incidence are exemplifiedin Table 1.

TABLE 1 Wavelength Penetration depth [nm] [nm] 633 2600 532 930 488 490458 280 405 98 355 9.3 244 5.6

The values in the table account for the field absorption both inillumination and collection paths.

This method is relatively easy to interpret for planar films, but itsapplication to structured samples can be highly misleading. Theelectromagnetic (EM) field distribution inside a structure can have avery complicated distribution, dependent in intricate ways on theinteraction between the electromagnetic field and the structurecharacteristics. In these cases, the measured spectrum represents thematerial properties at those locations in the structure which contributemost to the Raman signal. These indeed depend on the wavelength, but byno means can be easily related to the simple ‘penetration depth’concept.

In this connection, reference is made to FIGS. 3a-3c exemplifyingposition-dependence of the contribution to the main-Si-peak in the Ramansignal, for a simple grating structure. FIG. 3c schematicallyillustrates a modeled structure formed by SiO₂ layer on a patterned Silayer. Measured Raman signal from Si grating, corresponding towavelengths of λ=405 nm and λ=532 nm, are shown respectively in FIG. 3aand FIG. 3b . It should be noted that Raman signal only originates fromthe grating structure (where there is Si), and not from the SiO₂surrounding it.

According to the invention, a model-based approach is used, implementedto highly-flexible optical arrangement allowing acquisition of amultiplicity of different information channels, to allow both blanketand on-structure profiling capability (both vs. depth and/or laterallocation). In this connection, reference is made to FIG. 4 exemplifyinga flow diagram 10 of the model-based method of the invention. Forsimplicity, this approach can be split into few steps; these are not allnecessary for all implementations, some uses not involving all of thesesteps are described below. However, these step represent the mainbuilding blocks of the method of the invention.

First, according to this method a ‘Raman-contribution efficiency’ (RCE)is defined as specifying the position-dependent contribution to theRaman signal. This property depends on the measured structurecharacteristics (dimensions, materials), the excitation wavelength andthe characteristics of the illumination and collection channels (as willbe described below).

Raman-contribution efficiency for a measured structure is calculated(step 12). This calculation may optionally be assisted (step 14) byinformation about the structure obtained/measured from other metrologytools and/or test sites, e.g. OCD\SEM\TEM to provide dimensionalcharacterization, ellipsometry\XPS\SIMS for material characterization,etc.

Data about a variety of n measurement conditions is provided (step 16),and the Raman-contribution efficiency distributions across the structureRCE₁(x,y,z), RCE₂(x,y,z), . . . RCE_(n)(x,y,z) are calculated for the nmeasurement conditions, respectively, typically illumination/collectionconditions. These may include different angles of incidence (AOIs),wavelengths, polarizations, pupil shaping options, etc. Each differenti-th configuration provides a different distribution of theRCE_(i)(x,y,z) across the structure.

Then, a subset of the calculated configurations, RCE_(n-j)−RCE_(n-k),where j and k are integers, j≥k, is chosen (step 18), so as to gaininformation on the measured parameter distribution. Deriving theparameter distribution inside the structure from the set of measurement(step 20) can be accomplished using standard algorithms (e.g.deconvolution methods).

As an example, a simple approach to implement such derivation can bebased on a linear scheme: a set of measured Raman intensities I_(i) iscollected. Each is known to be related to the parameter distributioninside the structure through its RCE, namely:

I _(i)=∫RCE_(i)(x,y)P(x,y)dxdy.

By defining some spatial sampling of the measured structure, thisrelation can be written in matrix form:

I _(i) =M _(i,j) P _(j) or equivalently {right arrow over(I)}={circumflex over (M)}{right arrow over (P)}.

Here, the index j relates to different spatial locations and the index irelates to a different measurement. As both I and M are known (throughthe measurement and the modeling engine correspondingly), the spatialdistribution of the parameter can be directly obtained using RMSsolution:

{right arrow over (P)}={circumflex over (M)} ⁻¹ {right arrow over (I)}.

Many other algorithmic methods are available, allowing more stable andwell-controlled solutions.

This methodology can be applied to any measurable property, such asstress, composition, crystallinity, which are just a few non-limitingexamples.

It should be noted that the above-exemplified technique does notnecessarily has to be applied to a set of measurements. In practice,this approach can be used to find a single, optimized measurement schemeproviding highlighted sensitivity to a parameter of interest. Theprinciples of the invention do not relate to obtaining fullacross-structure profile information using a single measured Ramanspectrum, but this way the most important information can be gained withshort acquisition times. Alternatively, simultaneous acquisition ofRaman spectra for multiple AOIs can be measured using k-space imagingtechniques.

This is exemplified in FIG. 5 showing a block diagram of a measurementsystem 100 utilizing flexible Raman metrology measurement schemes. Asdescribed, such flexibility used in conjunction with advanced modelingtools, allows the improved performance, as well as altogether newcapabilities (e.g. profiling). System 100 includes a control system 106which is configured to receive input measured data indicative of Ramanspectrum or spectra measured on at least a part of a sample 105 usingone or more measurement schemes implemented in an optical system; andprocess this measured data by performing the above-described techniqueof the invention.

Generally, the measured data may be processed and analyzed in real time,in which case the control system 106 may receive the measured datadirectly from the output of the optical measurement system; or may beanalyzed off line in which case the measured data source may beconstituted by an externa storage device. For example, the measured datafrom a specific type of structure may be analyzed off line, thispre-calculated data may form a parameter-dependent ‘library’ oftheoretical spectra, in order to select the predetermined (optimal)measurements scheme for measuring structure parameter(s) of interest tobe used for controlling the process of manufacture of the structures ofsaid type.

The optical measurement system includes a light source system 102defining an illumination channel IC, and a detection system 104 defininga collection channel CC, and also includes a light affecting unitlocated in/associated with at least one of illumination and collectionchannels. In this non limiting example, the system includes both a lightillumination affecting unit 108 and a light collection affecting unit110. The Illumination and collection affecting units are configured foraffecting illumination and collection conditions. Such unit may includelight propagation affecting optics for affecting the condition of lightpropagating along the respective channel. The illumination affectingunit 108 may include (e.g. in addition to the light propagationaffecting optics) a controller for controlling operation of a lightsource system; alternatively or additionally such controller may be partof the control system 106.

The control system 106 is generally a computer system configured forcommunication with measured data provider (this may be wires and/orwireless communication, using any known suitable technique); and mayalso be configured for managing/controlling the measurements withdifferent measurement schemes in which case the control unit is alsoconfigured to communicate with at least some elements of the opticalmeasurement system (this may be wires and/or wireless communication,using any known suitable technique). As shown in the present example,the control system 106 may include illumination controller 106Aassociated with the illumination affecting unit 108 and/or light sourcesystem 102; a collection controller 106B associated with the collectionaffecting unit 110; and a data processor utility 106C. The latter isconfigured (preprogrammed with a specifically designed software product)to carry out the above-described method for processing data indicativeof measured Raman spectrum or spectra and determining the parameter(s)distribution inside the sample 105.

The efficiency of the above described approach depends on themeasurement flexibility allowed by the measurement system. Degrees offreedom added to the optical path can allow improved fine tuning of themeasurement to the requested metrological aim. FIG. 6 illustrates, in aself-explanatory manner, specific but not limiting example of theconfiguration of the optical system 200 allowing such considerableflexibility, including polarization control (including measurement offull Raman-Mueller matrix), pupil shaping at illumination andcollection, multiple wavelengths, k-space imaging etc. To facilitateunderstanding the main functional assemblies that are common in theFIGS. 5 and 6 are identified by the same reference numbers.

In system 200 of FIG. 6, the light source system 102 includes n lightsources (e.g. lasers) each for generating a light beam of a differentwavelengths; and includes/is associated with n beam conditioning unitsin light paths of the n light beams, respectively; and a laser beamselection unit (being optical and/or electronic unit) for selecting theexcitation (illuminating) wavelength. The beam conditioning can includespectral filtering and/or polarization and/or spatial filtering and/orbeam expansion and/or collimation. Such beam conditioning units are partof the illumination affecting unit 108. In this example, theillumination affecting unit 108 further includes polarization rotationassembly (e.g. variable λ/λ plate) and aperture variation assembly. Inother words, the illumination affecting unit 108 is configured to enablevariety of illumination wavelengths, polarization conditions, andangular propagation of the illumination. The collection affecting unit110 is configured to provide variety of polarization conditions,spectral filtering and angular propagation of the light being collectedfrom the sample.

(ii) Metrology of Stress Distribution Inside a Structure, AllowingSeparation of Different Stress Components

Stress metrology is a standard aim for Raman spectroscopy. The crystalstrain, accompanying internal stress, affects the inter-atomic forces,leading to a corresponding change in the vibration frequencies. Thesechanges are directly probed by Raman spectroscopy, through the shift inthe Raman peaks locations. Different methods exist to separatestress/strain from other characteristics which affect the peakslocations (e.g. composition, doping).

It can be shown that normal-incidence Raman metrology is predominantlysensitive to the z component of the crystal strain (G. H. Loechelt etal., Polarized off-axis Raman spectroscopy: A technique for measuringstress tensors in semiconductors, J. App. Phys. 86, 6164 (1999)). Forsimple non-patterned films, some sensitivity to the in-plain straincomponents can be obtained using oblique illumination and/or collectionchannels, or very high numerical aperture measurement setups. However,these methods are completely irrelevant when measuring in patternedstructures.

Similarly to the methodology described above for spatial profiling, thepresent invention provides for using modeling tools, in conjunction withselected modes of measurement (illumination/collection AOI and pupilshaping, wavelengths, polarizations, etc.), to identify a preferredmetrology scheme (or combination of such schemes) to provide optimalsensitivity to the strain orientation(s) of interest. Alternatively, itis possible to identify the optimal metrology scheme experimentally, byfirst utilizing a large set of varied measured information channels, andthen identification of the most beneficial set (that one which providesbest precision, accuracy and/or any other attribute).

The full vectorial strain distribution inside the structure can bederived from a set of such measurements using standard algorithms. Forclarity, a possible approach is exemplified below, while it should beunderstood that many other algorithmic methods can be implemented. Thesame approach can be used in an identical manner for across-structureprofiling of any other property to which the Raman signal is sensitive(e.g. composition, doping).

Each measured dataset for RCE depends on the strain distribution throughsome known weighting over different parts of the structure (this weightis known based on the modeling tool). Explicitly, we can write:

I(C _(i))=∫RCE^(C) ^(i) (x,y,z)S[P(x,y,z)]dxdydz

Here, C_(i) represents the measured channel/measurement scheme definedby a configuration of illuminating and collected light conditions (AOI,polarizations, azimuths, etc.); (x,y,z) are the spatial coordinates;RCE^(Ci) is the Raman Contribution Efficiency for this channel, definedabove; P is the position-dependent parameter (strain in the presentcase); and S[P(x,y,z)] is the associated Raman signal for thisdistribution of the parameter, obtained by modeling.

The rationale behind this expression is that the Raman signal sums overthe individual contributions from different parts of the structure, witheach contribution being dependent on the local strain, and weighedaccording to the local RCE. It should be noted that this expression isan approximation for the more rigorous derivation, and is used here forsimplicity, to clarify the proposed method for strain distributioncharacterization.

In matrix form, this expression can be written as

I _(i)={right arrow over (RCE)}_(i) ·{right arrow over (S)}[P],

where the index i stands for the measured channel, and the vectorizationis across the entire spatial domain (i.e. different entries in thevectors correspond to different positions).

Considering now a set of measured channels, leading to a set of measuredsignals {right arrow over (I)}, we can write

{right arrow over (I)}=

·{right arrow over (S)}[P],

where

is a matrix holding the weighting across structure for each measuredchannel, known from the model.

Using the measured signal {right arrow over (I)} and the calculated

, the spatial strain distribution can be estimated using

{right arrow over (S)}[P]=(

)⁻¹ ·{right arrow over (I)}.

(iii) Use of Modeling/Algorithmic Tools for During-Measurement-Feedback

The approach described above concerns the use of modeling capabilitiesto pre-define a measurement sequence for the application of interest,namely what channel combination to use, how to optimize the measurementsequence, etc. This approach can be extended to allow modifications tothe measurement flow according to the measured results. Severalvariations are possible for this implementation, as follows:

The interpreted results from a previous Raman measurement can be used.More specifically, a first set of Raman measurements (one or several)provides information on the measured characteristics. Using modelingcapabilities, it is then possible to change the measurementcharacteristics (wavelength, AOI, polarizations, etc.) so as to provideimproved performance of the measurement. This method can be implementedfor consecutive measurements performed on other sites, or for repeatedmeasurements on the same site.

An example of specific interest for such usage of metrological feedbackis the identification of stress relaxation. When growing a crystallinelayer (e.g. epitaxially-grown SiGe or GaAs) on a substrate made out of adifferent material (e.g. Si), crystal strain is developed due to thedifferent crystal lattice constants. Depending on the growth conditionsand the layer thickness, strain relaxation can potentially occur, in theform of alternating relaxed and strained regions. Such strain relaxationcan be disastrous to the performance of the fabricated device, andrequires adequate monitoring. Such metrology can be provided using Ramanspectroscopy based on the concept of during-measurement-feedback, asfollows: Local strain and composition can be deduced from the Ramanmeasurement. In extreme cases, this measurement alone may be enough toidentify significant strain relaxation. However, if relaxation is notoverly severe, the measurement will only identify that relaxation issuspected. Using a model-based tool, the strain reading can be analyzedto identify such relaxation-suspected cases. Modeling is especiallycritical for on-structure measurements, when different strain componentscan confound the measurement. When a sample suspected of strainrelaxation is identified, another set Raman measurements can be taken atadjacent locations. As noted, it is a typical characteristic ofstrain-relaxed samples that the strain becomes inhomogeneous, expressingregions of high and low strain. If indeed such variability isidentified, the sample will be classified as strain-relaxed.

(iv) Dimensional Metrology

One capability of unique interest allowed by adding modelingcapabilities to Raman spectroscopy is dimensional metrology. Indeed,such capabilities require a multifaceted modeling tool/methods,involving both comprehensive characterization of the electromagneticfield penetration into and out of the structure, as well as modeling ofthe Raman signal creation inside the structure. Such a path can providehighly sensitive information on the measured structure.

Evidence that dimensional factors affect the measured Raman signal areknown in the literature, for example from the following publications: A.K. Arora et al., Raman spectroscopy of optical phonon confinement innanostructured materials, J. of Raman Spectroscopy 38, 604 (2007); B.Kaleli et al., Strain characterization of FinFETs using Ramanspectroscopy, Thin Solid Films 31497 (2013); T. Nuytten et al.,Edge-enhanced Raman scattering in narrow sGe fin field-effect transistorchannels, App. Phys. Lett. 106, 033107 (2015). On specific cases (e.g.nanowires), the Raman signal has been found to provide dimensionalinformation on a dimensional characteristic of the structure (e.g.nanowire diameter [J. Liu et al., Raman spectrum of array-orderedcrystalline silicon nanowires, Physica E 23, 221 (2004); R. P. Wang etal., Raman spectral study of silicon nanowires: High-order scatteringand phonon confinement effects, Phys. Rev. B 61, 16827 (2000)]).

However, through general modeling capabilities, akin to that utilized inOCD metrology, a similar methodology to OCD can be used to solve theinverse-problem of deducing the dimensional properties from themeasurements. In this method, the measured signal is compared to thatcalculated from the modeling tool, for some assumed properties(dimensions, materials) of the test structure. When good fit is obtainedbetween the measured and calculated signal, it is deduced that themeasured structure has similar characteristics to the correspondingcalculated one. Similarly to common practice in OCD metrology, thetheoretical Raman signals can be calculated in real-time (‘real-timeregression’) or pre-calculated to form a parameter-dependent ‘library’of theoretical spectra.

We claim:
 1. A method for Raman spectroscopy, the method comprises:operating a Raman spectroscope.